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Impact of positive end-expiratory pressure on renal resistive index in mechanical ventilated patients.

Authors :
Fogagnolo A
Grasso S
Morelli E
Murgolo F
Di Mussi R
Vetrugno L
La Rosa R
Volta CA
Spadaro S
Source :
Journal of clinical monitoring and computing [J Clin Monit Comput] 2024 Oct; Vol. 38 (5), pp. 1145-1153. Date of Electronic Publication: 2024 May 21.
Publication Year :
2024

Abstract

Purpose: Growing evidence shows the complex interaction between lung and kidney in critically ill patients. The renal resistive index (RRI) is a bedside measurement of the resistance of the renal blood flow and it is correlated with kidney injury. The positive end-expiratory pressure (PEEP) level could affect the resistance of renal blood flow, so we assumed that RRI could help to monitoring the changes in renal hemodynamics at different PEEP levels. Our hypothesis was that the RRI at ICU admission could predict the risk of acute kidney injury in mechanical ventilated critically ill patients.<br />Methods: We performed a prospective study including 92 patients requiring mechanical ventilation for ≥ 48 h. A RRI ≥ 0.70, was deemed as pathological. RRI was measured within 24 h from ICU admission while applying 5,10 and 15 cmH <subscript>2</subscript> O of PEEP in random order (PEEP trial).<br />Results: Overall, RRI increased from 0.62 ± 0.09 at PEEP 5 to 0.66 ± 0.09 at PEEP 15 (p < 0.001). The mean RRI value during the PEEP trial was able to predict the occurrence of AKI with AUROC = 0.834 [95%CI 0.742-0.927]. Patients exhibiting a RRI ≥ 0.70 were 17/92(18%) at PEEP 5, 28/92(30%) at PEEP 10, 38/92(41%) at PEEP 15, respectively. Thirty-eight patients (41%) exhibited RRI ≥ 0.70 at least once during the PEEP trial. In these patients, AKI occurred in 55% of the cases, versus 13% remaining patients, p < 0.001.<br />Conclusions: RRI seems able to predict the risk of AKI in mechanical ventilated patients; further, RRI values are influenced by the PEEP level applied.<br />Trial Registration: Clinical gov NCT03969914 Registered 31 May 2019.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
1573-2614
Volume :
38
Issue :
5
Database :
MEDLINE
Journal :
Journal of clinical monitoring and computing
Publication Type :
Academic Journal
Accession number :
38771490
Full Text :
https://doi.org/10.1007/s10877-024-01172-z